Approved Research

Genetic-Environmental Factors Causing Recurrent Miscarriages Through Gender Synergistic Effect

Lay summary

Our research project aims to investigate the complex causes behind recurrent miscarriages, a reproductive health issue affecting 1-2% of couples trying to conceive. We will focus on understanding how genetic and environmental factors and the interaction between male and female partners might contribute to recurrent miscarriages. By using advanced machine learning algorithms, we will analyze a comprehensive dataset, including genomic, medical examination, and phenotypic data, to identify any differences between couples experiencing recurrent miscarriages and those who do not.

The scientific rationale for this project stems from the fact that while some causes of recurrent miscarriages, such as chromosomal abnormalities, hormonal imbalances, and uterine malformations, are known, many cases remain unexplained. Previous studies have suggested that genetic and environmental factors may play a role in recurrent miscarriage, but most research has focused on either male or female factors separately. Our study will address this gap by examining the potential synergistic effects of genetic and environmental factors between partners and the role of male sperm quality and quantity in recurrent miscarriages.

The duration of this project will depend on several factors, including the time required for data collection and preprocessing, the complexity of machine learning algorithms used, and the need for additional data analysis or validation. We estimate that the project could take approximately 24-36 months to complete, allowing for thorough data analysis and interpretation of results.

The public health impact of this research is significant, as it aims to improve our understanding of the complex causes behind recurrent miscarriages. By identifying potential genetic and environmental factors and their interactions, our findings could inform the development of more effective interventions and treatments for couples affected by recurrent miscarriages. This research would ultimately lead to improved reproductive health and well-being, reduce the emotional and financial burden associated with recurrent miscarriages, and contribute to a broader understanding of factors influencing reproductive health in the general population.

Our research project explores the interplay between genetic and environmental factors and gender synergistic effects in causing recurrent miscarriages. By utilizing machine learning algorithms and analyzing comprehensive datasets, we aim to provide new insights into this critical reproductive health issue and pave the way for more effective interventions and treatments.